Package index • missingHE

Package Overview

missingHE missingHE-package: missingHE: Missing Cost Effectiveness Models

Model Fitting

Functions for fitting Bayesian missingness models to individual-level CEA data.

selection(): Bayesian Selection Models
pattern(): Bayesian Pattern Mixture Models
hurdle(): Bayesian Hurdle Models
lmdm(): Bayesian Longitudinal Missing Data Models

Plotting & Diagnostics

Functions for visualising model fit, MCMC convergence outputs.

plot(<missingHE>): Plot method for the imputed data
diagnostic(): Diagnostic checks for assessing MCMC convergence of a Bayesian model
ppc(): Posterior predictive checks for assessing the fit to the observed data of a Bayesian model
postsum(): Postsum method for inspecting summary posterior estimates of a Bayesian model

Summaries & Outputs

Functions for extracting posterior summaries and model comparisons.

summary(<missingHE>): Summary method for objects in the class missingHE
print(<missingHE>): Print method for objects in the class missingHE
coef(<missingHE>): Extract regression coefficient estimates from objects in the class missingHE
pic(): Predictive information criteria for a Bayesian model

Data

Example datasets included in the package.

MenSS: MenSS economic data on STIs
PBS: PBS economic data on intellectual disability and challenging behaviour